AIMC Topic: Middle Aged

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Use of a Preliminary Artificial Intelligence-Based Laryngeal Cancer Screening Framework for Low-Resource Settings: Development and Validation Study.

JMIR formative research
BACKGROUND: Early-stage diagnosis of laryngeal cancer significantly improves patient survival and quality of life. However, the scarcity of specialists in low-resource settings hinders the timely review of flexible nasopharyngoscopy (FNS) videos, whi...

Evolving Health Information-Seeking Behavior in the Context of Google AI Overviews, ChatGPT, and Alexa: Interview Study Using the Think-Aloud Protocol.

Journal of medical Internet research
BACKGROUND: Online health information seeking is undergoing a major shift with the advent of artificial intelligence (AI)-powered technologies such as voice assistants and large language models (LLMs). While existing health information-seeking behavi...

MiThyCA: A Computational Pathology Pipeline for the Identification of Microscopic Foci of Papillary Thyroid Carcinoma-Like Nuclear Features with AI in Whole-Slide Histological Images.

Endocrine pathology
The histological identification of papillary thyroid carcinoma (PTC) is straightforward for experienced endocrine pathologists. The increase in radical thyroidectomies led to a raise in the rate of postoperative incidental subcentimeter PTC foci and ...

Natural lithium isotope variations in serum after lithium administration as a novel biomarker for differentiating schizophrenia and bipolar disorder.

Translational psychiatry
Accurate differentiation of schizophrenia (SZ) and bipolar disorder (BD) is crucial for effective clinical management. However, current diagnostic methods, which rely heavily on subjective assessments, are prone to high rates of misdiagnosis. This st...

Application of machine learning to predict delayed fecundability among women in sub-Saharan Africa.

Reproduction & fertility
ABSTRACT: Delayed fecundability, defined as trying to conceive for ≥12 months without success, is a growing global concern due to the threat of fertility rates falling below the replacement level. This study aimed to predict delayed fecundability and...

Cardiovascular risk prediction and influencing predictors identification among Bangladeshi individuals using machine learning algorithms and association rule mining.

PloS one
BACKGROUND: Cardiovascular disease (CVD) encompasses a group of disorders that affect the heart and blood vessels, making it one of the leading causes of death globally, including in Bangladesh. Applying predictive modeling for the early identificati...

Estimated glucose disposal rate predicts frailty through diabetes: Evidence from machine learning and mediation models in NHANES.

PloS one
OBJECTIVE: As an emerging insulin resistance marker, the relationship between estimated glucose disposal rate (eGDR) and frailty needs further exploration. This study examines the eGDR-frailty link, develops a machine learning predictive model to add...

Machine learning-based identification of small RNA signatures in aqueous humor as a step toward precision diagnosis of glaucoma.

Annals of medicine
BACKGROUND: Glaucoma is a progressive neurodegenerative disease of the optic nerve and one of the leading causes of irreversible blindness worldwide. Small RNAs (including miRNAs) play an important role in the pathogenesis of the disease. Despite ext...

Investigating the relationship between blood factors and HDL-C levels in the bloodstream using machine learning methods.

Journal of health, population, and nutrition
INTRODUCTION: The study investigates the relationship between blood lipid components and metabolic disorders, specifically high-density lipoprotein cholesterol (HDL-C), which is crucial for cardiovascular health. It uses logistic regression (LR), dec...

Leveraging machine learning to predict mosquito bed net utilization among women of reproductive age in sub-Saharan Africa.

Malaria journal
BACKGROUND: Malaria remains a major public health challenge, particularly in sub-Saharan Africa, where women of reproductive age are especially vulnerable during pregnancy and childbirth. To identify key predictors and improve predictive accuracy, ma...